Preliminaries Last updated: 2022-04-10

Welcome to the Fundamentals of Cloud Computing Course Web Page.

Course information

Instructor Associate Professor Dr. Mihailescu Marius Iulian
Teaching Assistant Associate Professor Dr. Mihailescu Marius Iulian

Course description

The primary goal of this course is to introduce ideas relevant to cloud computing analysis, design, and implementation. The student will be able to comprehend the necessary theoretical underpinnings for computing and storage clouds environments after completing the course. The student will start to be familiar with the technologies and development methods for apps that will be made available through cloud computing environments. At the dn of this course, the student will be able to build cloud applications using PaaS software and design cloud infrastructures using IaaS software.

Course Objective(s)

The main objective(s) of the course and the expected outcomes are:

  • Having a basic introduction regarding the basic concepts and terminology used in cloud computing.
  • Getting used with areas and applications related to cloud technologies.
  • Being able to perform evaluation in terms of efficiency on a long term, performing economical and feasibility studies.
  • Getting familiar with cloud computing infrastructures.
  • Learning about security, how to perform a proper deployment of the applications, scalability, in the cloud infrastructure context.
  • Being able to write complex programs for different topics, such as databases, distributed systems, cryptography, artificial intelligence or machine learning.

Course Structure

# Course Title Date and Time
01 Introduction in Distributed Systems October 5th, 2022

Laboratory Structure

# Laboratory Title Date and Time
01 Example of Distributed System October 5th, 2022


The final mark is composed from mid-terms and final exam. See the details from below.

The mid-terms represents 50% from the final mark.

  • 1st mid-term (10%) - Course: October 25th, 2022
  • 2nd mid-term (20%) - Laboratory: November 15th, 2022
  • 3rd mid-term (20%) - Laboratory: November 29th, 2022

For the 1st mid-term the student will receive 30 questions, each question will have 3 points (30 * 3p = 90p). For this mid-term test (evaluation) 10p ex-officio point will be received.

The final exam will represent 50% from the final mark.


  • Kim, Haengkon, and Roger Lee, editors. Software Engineering in IoT, Big Data, Cloud and Mobile Computing. Springer, 2021.
  • Lisdorf, Anders. Cloud Computing Basics: A Non-Technical Introduction. Apress, 2021.
  • Coombs, Ted. Cloud Security For Dummies. 1st ed., John Wiley & Sons Inc, 2022.
  • McHaney, Roger. Cloud Technologies: An Overview of Cloud Computing Technologies for Managers. First edition, Wiley, 2021.
  • Millard, Christopher, editor. Cloud Computing Law. 2nd ed., Oxford University Press, 2021.
  • Lynn, Theo, et al. Data Privacy and Trust in Cloud Computing: Building Trust in the Cloud through Assurance and Accountability. Springer, 2021.
  • Misra, Sanjay, et al., editors. Artificial Intelligence for Cloud and Edge Computing. Springer, 2022.
  • Pal, Souvik, et al. Cloud Computing Solutions: Architecture, Data Storage, Implementation and Security. Scrivener Publishing ; John Wiley & Sons, Inc., 2022.


The list of courses is:

  • C01 - Introduction in Distributed Systems

C01 - Introduction in Distributed Systems

Course objective
In this course we will learn about functional programming, why it is important, its strenghts, advantages and disadvantages, compared with other programming paradigms. We will take into consideration examples from other programming paradigms and languages and compare them with functional programming.



The list of laboratories is:

  • L01 - Example of Distributed System

L01 - Example of Distributed System

Laboratory objective
In this laboratory will learn how to resolve exercises using a formal system in mathematical logic for expressing computation based on function abstraction and application utilizing variable binding and substitution, which is known as lambda calculus. It is a general-purpose computational model that can imitate any Turing computer.